Difference between revisions of "ApCoCoA-1:CharP.IMNLASolve"
(New page: <command> <title>CharP.GBasisF2</title> <short_description>Computing the unique <tt>F_2-</tt>rational zero of a given polynomial system over <tt>F_2</tt>.</short_description> <synt...) |
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<command> | <command> | ||
− | <title>CharP. | + | <title>CharP.IMNLASolve</title> |
− | <short_description> | + | <short_description>Computes the unique <tt>F_2-</tt>rational zero of a given polynomial system over <tt>F_2</tt>.</short_description> |
<syntax> | <syntax> | ||
− | CharP. | + | CharP.IMNLASolve(F:LIST):LIST |
</syntax> | </syntax> | ||
<description> | <description> | ||
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<par/> | <par/> | ||
− | This function computes the unique zero in <tt>F_2^n</tt> of a polynomial system over <tt>F_2 </tt>. It uses | + | This function computes the unique zero in <tt>F_2^n</tt> of a polynomial system over <tt>F_2</tt>. It uses <tt>I</tt>mproved <tt>M</tt>utant <tt>NLA</tt>-Algorithm to find the unique zero. The Improved Mutant <tt>NLA</tt>-Algorithm generates a sequence of linear systems to solve the given system. The Improved Mutant <tt>NLA</tt>-Algorithm can find the unique zero only. If the given polynomial system has more than one zeros in <tt>F_2^n </tt> then this function does not find any zero. In this case a massage for non-uniqueness will be displayed to the screen after reaching the maximum degree bound. In fact Improved Mutant NLA-Algorithm is the NLA-Algorithm with improved mutant strategy. It uses <ref>ApCoCoA-1:LinAlg.EF|LinAlg.EF</ref> for gaussian elimination. |
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<itemize> | <itemize> | ||
<item>@param <em>F:</em> List of polynomials of given system.</item> | <item>@param <em>F:</em> List of polynomials of given system.</item> | ||
− | <item>@return | + | <item>@return Possibly the unique solution of the given system in <tt>F_2^n</tt>. </item> |
</itemize> | </itemize> | ||
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-- Then we compute the solution with | -- Then we compute the solution with | ||
− | CharP. | + | CharP.IMNLASolve(F); |
-- And we achieve the following information on the screen together with the solution at the end. | -- And we achieve the following information on the screen together with the solution at the end. | ||
---------------------------------------- | ---------------------------------------- | ||
− | + | ||
− | + | The size of Matrix is: | |
− | + | No. of Rows=4 | |
− | + | No. of Columns=11 | |
− | + | Applying Gaussian Elimination for finding Mutants... | |
− | + | Gaussian Elimination Compeleted. | |
− | + | Finding Variable: x[4] | |
− | + | The size of Matrix is: | |
− | Gaussian Elimination Compeleted | + | No. of Rows=11 |
− | + | No. of Columns=5 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=11 | |
− | + | No. of Columns=5 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=4 | |
− | + | No. of Columns=11 | |
− | + | Applying Gaussian Elimination for finding Mutants... | |
− | + | Gaussian Elimination Compeleted. | |
− | Gaussian Elimination Completed. | + | No. of New Mutants found = 0 |
− | + | The size of Matrix is: | |
− | + | No. of Rows=11 | |
− | + | No. of Columns=9 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | Gaussian Elimination Completed. | + | No. of Rows=11 |
− | + | No. of Columns=9 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=8 | |
− | + | No. of Columns=11 | |
− | + | Applying Gaussian Elimination for finding Mutants... | |
− | Gaussian Elimination Compeleted | + | Gaussian Elimination Compeleted. |
− | + | No. of New Mutants found = 1 | |
− | + | The total No. of Mutants found are = 1 | |
− | + | The No. of Mutants of Minimum degree (Mutants used) are = 1 | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=11 | |
− | + | No. of Columns=12 | |
− | Gaussian Elimination Completed. | + | Applying Gaussian Elimination to check solution coordinate... |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=11 | |
− | + | No. of Columns=12 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | Gaussian Elimination Completed. | + | x[4] = 1 |
− | + | Finding Variable: x[3] | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=7 | |
− | + | No. of Columns=10 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | x[3] = 0 | |
− | Gaussian Elimination Compeleted | + | Finding Variable: x[2] |
− | + | The size of Matrix is: | |
− | + | No. of Rows=4 | |
− | + | No. of Columns=5 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=4 | |
− | + | No. of Columns=5 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | x[2] = 1 | |
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− | Gaussian Elimination Completed. | ||
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− | Gaussian Elimination Completed. | ||
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− | Gaussian Elimination Completed. | ||
− | x[3] = 0 | ||
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− | Gaussian Elimination Completed. | ||
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− | Gaussian Elimination Completed. | ||
− | x[2] = 1 | ||
[0, 1, 0, 1] | [0, 1, 0, 1] | ||
Line 200: | Line 120: | ||
-- Then we compute the solution with | -- Then we compute the solution with | ||
− | CharP. | + | CharP.IMNLASolve(F); |
-- And we achieve the following information on the screen. | -- And we achieve the following information on the screen. | ||
---------------------------------------- | ---------------------------------------- | ||
− | + | ||
− | + | The size of Matrix is: | |
− | + | No. of Rows=4 | |
− | + | No. of Columns=9 | |
− | + | Applying Gaussian Elimination for finding Mutants... | |
− | + | Gaussian Elimination Compeleted. | |
− | + | Finding Variable: x[4] | |
− | + | The size of Matrix is: | |
− | Gaussian Elimination Compeleted | + | No. of Rows=9 |
− | + | No. of Columns=4 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=9 | |
− | + | No. of Columns=4 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=3 | |
− | + | No. of Columns=9 | |
− | + | Applying Gaussian Elimination for finding Mutants... | |
− | + | Gaussian Elimination Compeleted. | |
− | Gaussian Elimination Completed. | + | No. of New Mutants found = 0 |
− | + | The size of Matrix is: | |
− | + | No. of Rows=14 | |
− | + | No. of Columns=8 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | Gaussian Elimination Completed. | + | No. of Rows=14 |
− | + | No. of Columns=8 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=7 | |
− | + | No. of Columns=14 | |
− | + | Applying Gaussian Elimination for finding Mutants... | |
− | Gaussian Elimination Compeleted | + | Gaussian Elimination Compeleted. |
− | + | No. of New Mutants found = 2 | |
− | + | The total No. of Mutants found are = 2 | |
− | + | The No. of Mutants of Minimum degree (Mutants used) are = 2 | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=10 | |
− | + | No. of Columns=14 | |
− | Gaussian Elimination Completed. | + | Applying Gaussian Elimination to check solution coordinate... |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=10 | |
− | + | No. of Columns=14 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | Gaussian Elimination Completed. | + | The size of Matrix is: |
− | + | No. of Rows=13 | |
− | + | No. of Columns=10 | |
− | + | Applying Gaussian Elimination for finding Mutants... | |
− | + | Gaussian Elimination Compeleted. | |
− | + | No. of New Mutants found = 0 | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=10 | |
− | Gaussian Elimination Compeleted | + | No. of Columns=9 |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=10 | |
− | + | No. of Columns=9 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=8 | |
− | + | No. of Columns=10 | |
− | + | Applying Gaussian Elimination for finding Mutants... | |
− | + | Gaussian Elimination Compeleted. | |
− | + | No. of New Mutants found = 0 | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=14 | |
− | + | No. of Columns=24 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | The size of Matrix is: | |
− | + | No. of Rows=14 | |
− | + | No. of Columns=24 | |
− | + | Applying Gaussian Elimination to check solution coordinate... | |
− | + | Gaussian Elimination Completed. | |
− | + | x[4] = NA | |
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− | Gaussian Elimination Completed. | ||
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− | Gaussian Elimination Completed. | ||
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− | Gaussian Elimination Compeleted | ||
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− | Gaussian Elimination Completed. | ||
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− | Gaussian Elimination Completed. | ||
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− | Gaussian Elimination Compeleted | ||
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− | Gaussian Elimination Completed. | ||
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− | Gaussian Elimination Completed. | ||
− | x[4] = NA | ||
Please Check the uniqueness of solution. | Please Check the uniqueness of solution. | ||
The Given system of polynomials does not | The Given system of polynomials does not | ||
seem to have a unique solution or it has | seem to have a unique solution or it has | ||
no solution over the finite field F2. | no solution over the finite field F2. | ||
− | |||
</example> | </example> | ||
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</description> | </description> | ||
<seealso> | <seealso> | ||
− | <see>CharP.MXLSolve</see> | + | <see>ApCoCoA-1:CharP.MXLSolve|CharP.MXLSolve</see> |
− | <see>Introduction to CoCoAServer</see> | + | <see>ApCoCoA-1:Introduction to CoCoAServer|Introduction to CoCoAServer</see> |
− | <see>Introduction to Groebner Basis in CoCoA</see> | + | <see>ApCoCoA-1:Introduction to Groebner Basis in CoCoA|Introduction to Groebner Basis in CoCoA</see> |
− | <see>CharP.GBasisF2</see> | + | <see>ApCoCoA-1:CharP.GBasisF2|CharP.GBasisF2</see> |
− | <see>CharP.XLSolve</see> | + | <see>ApCoCoA-1:CharP.XLSolve|CharP.XLSolve</see> |
− | <see>CharP.IMXLSolve</see> | + | <see>ApCoCoA-1:CharP.IMXLSolve|CharP.IMXLSolve</see> |
− | <see>CharP. | + | <see>ApCoCoA-1:CharP.MNLASolve|CharP.MNLASolve</see> |
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</seealso> | </seealso> | ||
<types> | <types> | ||
<type>apcocoaserver</type> | <type>apcocoaserver</type> | ||
− | <type> | + | <type>poly_system</type> |
− | |||
</types> | </types> | ||
− | <key>charP. | + | <key>charP.imnlasolve</key> |
− | <key> | + | <key>imnlasolve</key> |
<key>finite field</key> | <key>finite field</key> | ||
− | <wiki-category>Package_charP</wiki-category> | + | <wiki-category>ApCoCoA-1:Package_charP</wiki-category> |
</command> | </command> |
Latest revision as of 09:56, 7 October 2020
This article is about a function from ApCoCoA-1. |
CharP.IMNLASolve
Computes the unique F_2-rational zero of a given polynomial system over F_2.
Syntax
CharP.IMNLASolve(F:LIST):LIST
Description
Please note: The function(s) explained on this page is/are using the ApCoCoAServer. You will have to start the ApCoCoAServer in order to use it/them.
This function computes the unique zero in F_2^n of a polynomial system over F_2. It uses Improved Mutant NLA-Algorithm to find the unique zero. The Improved Mutant NLA-Algorithm generates a sequence of linear systems to solve the given system. The Improved Mutant NLA-Algorithm can find the unique zero only. If the given polynomial system has more than one zeros in F_2^n then this function does not find any zero. In this case a massage for non-uniqueness will be displayed to the screen after reaching the maximum degree bound. In fact Improved Mutant NLA-Algorithm is the NLA-Algorithm with improved mutant strategy. It uses LinAlg.EF for gaussian elimination.
@param F: List of polynomials of given system.
@return Possibly the unique solution of the given system in F_2^n.
Example
Use Z/(2)[x[1..4]]; F:=[ x[1]x[2] + x[2]x[3] + x[2]x[4] + x[3]x[4] + x[1] + x[3] + 1, x[1]x[2] + x[1]x[3] + x[1]x[4] + x[3]x[4] + x[2] + x[3] + 1, x[1]x[2] + x[1]x[3] + x[2]x[3] + x[3]x[4] + x[1] + x[4] + 1, x[1]x[3] + x[2]x[3] + x[1]x[4] + x[2]x[4] + 1 ]; -- Then we compute the solution with CharP.IMNLASolve(F); -- And we achieve the following information on the screen together with the solution at the end. ---------------------------------------- The size of Matrix is: No. of Rows=4 No. of Columns=11 Applying Gaussian Elimination for finding Mutants... Gaussian Elimination Compeleted. Finding Variable: x[4] The size of Matrix is: No. of Rows=11 No. of Columns=5 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=11 No. of Columns=5 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=4 No. of Columns=11 Applying Gaussian Elimination for finding Mutants... Gaussian Elimination Compeleted. No. of New Mutants found = 0 The size of Matrix is: No. of Rows=11 No. of Columns=9 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=11 No. of Columns=9 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=8 No. of Columns=11 Applying Gaussian Elimination for finding Mutants... Gaussian Elimination Compeleted. No. of New Mutants found = 1 The total No. of Mutants found are = 1 The No. of Mutants of Minimum degree (Mutants used) are = 1 The size of Matrix is: No. of Rows=11 No. of Columns=12 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=11 No. of Columns=12 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. x[4] = 1 Finding Variable: x[3] The size of Matrix is: No. of Rows=7 No. of Columns=10 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. x[3] = 0 Finding Variable: x[2] The size of Matrix is: No. of Rows=4 No. of Columns=5 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=4 No. of Columns=5 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. x[2] = 1 [0, 1, 0, 1]
Example
Use Z/(2)[x[1..4]]; F:=[ x[2]x[3] + x[1]x[4] + x[2]x[4] + x[3]x[4] + x[1] + x[2] + x[3] + x[4], x[2]x[3] + x[2]x[4] + x[3]x[4] + x[2] + x[3] + x[4], x[1]x[2] + x[2]x[3] + x[2]x[4] + x[3]x[4] + x[1] + x[2], x[1]x[2] + x[2]x[3] + x[2]x[4] + x[3]x[4] + x[1] + x[2] ]; -- Solution is not unique i.e. [0, 1, 1, 1], [0, 0, 0, 0], and [1, 1, 1, 1] are solutions -- Then we compute the solution with CharP.IMNLASolve(F); -- And we achieve the following information on the screen. ---------------------------------------- The size of Matrix is: No. of Rows=4 No. of Columns=9 Applying Gaussian Elimination for finding Mutants... Gaussian Elimination Compeleted. Finding Variable: x[4] The size of Matrix is: No. of Rows=9 No. of Columns=4 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=9 No. of Columns=4 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=3 No. of Columns=9 Applying Gaussian Elimination for finding Mutants... Gaussian Elimination Compeleted. No. of New Mutants found = 0 The size of Matrix is: No. of Rows=14 No. of Columns=8 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=14 No. of Columns=8 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=7 No. of Columns=14 Applying Gaussian Elimination for finding Mutants... Gaussian Elimination Compeleted. No. of New Mutants found = 2 The total No. of Mutants found are = 2 The No. of Mutants of Minimum degree (Mutants used) are = 2 The size of Matrix is: No. of Rows=10 No. of Columns=14 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=10 No. of Columns=14 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=13 No. of Columns=10 Applying Gaussian Elimination for finding Mutants... Gaussian Elimination Compeleted. No. of New Mutants found = 0 The size of Matrix is: No. of Rows=10 No. of Columns=9 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=10 No. of Columns=9 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=8 No. of Columns=10 Applying Gaussian Elimination for finding Mutants... Gaussian Elimination Compeleted. No. of New Mutants found = 0 The size of Matrix is: No. of Rows=14 No. of Columns=24 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. The size of Matrix is: No. of Rows=14 No. of Columns=24 Applying Gaussian Elimination to check solution coordinate... Gaussian Elimination Completed. x[4] = NA Please Check the uniqueness of solution. The Given system of polynomials does not seem to have a unique solution or it has no solution over the finite field F2.
See also
Introduction to Groebner Basis in CoCoA